🚀 Harnessing Google Cloud for Real-Time Problem Solving through Observability 🌐 📖 Overview: This session, led by Saurabh Mishra, dives into the principles and practices of observability on Google Cloud Platform (GCP). Learn how to gain actionable insights into system behavior, improve reliability, and tackle real-time challenges. 🔑 Key Takeaways: What is Observability? It's the ability to measure a system's internal states by analyzing its outputs. Key pillars: Metrics (what is happening), Logs (why it’s happening), and Traces (how it’s happening). Chaos Engineering Test system resilience by simulating controlled failures like pod disruptions or network delays. Learn to monitor and improve your system from these tests. Observability vs. Monitoring Monitoring: Reactive, tracks predefined metrics. Observability: Proactive, explores unknown system behaviors using a holistic approach. Google Cloud Operations Suite Tools like Cloud Monitoring, Logging, and Trace to improve observability and troubleshoot efficiently. Hands-On Lab Step-by-step demo on deploying and monitoring latency in a Google Kubernetes Engine (GKE) cluster. 🌟 Why It Matters: Enhance system reliability. Optimize operational costs. Gain better visibility into distributed systems. Improve troubleshooting speed. 💡 Challenges Discussed: Addressing data silos and alert fatigue. Managing data overload and integration complexities. 💻 Resources: Official GCP Observability Documentation: cloud.google.com/observability GitHub Lab Code: python-docs-samples